Human Visual System Based Enhanced AMBTC for Color Image Compression Using Interpolation

R. Kumar, Samayveer Singh, K. Jung
{"title":"Human Visual System Based Enhanced AMBTC for Color Image Compression Using Interpolation","authors":"R. Kumar, Samayveer Singh, K. Jung","doi":"10.1109/SPIN.2019.8711635","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel enhanced AMBTC image compression method for digital color images which uses the characteristics of human visual system. The proposed compression method first transforms the RGB image into YCbCr color space and then divides each component of the image into non-overlapping blocks. To improve the imperceptibility of caused distortion due to AMBTC compression, the proposed method computes four quantization levels and 32 bits bit-planes for luminance component (Y) blocks whereas the blocks of the remaining two components (i.e., Cb & Cr) are represented by two quantization levels and only 8 bits bit-planes. At the receiving end, the receiver can use interpolation technique to predict the remaining 8 bits of the bit-planes of Cb and Cr components. Thus, the proposed method provides better quality stego-image than the related existing methods, Further, the required bit-rate is also reduced for all the test images irrespective of their characteristics.","PeriodicalId":344030,"journal":{"name":"2019 6th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Signal Processing and Integrated Networks (SPIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIN.2019.8711635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

This paper proposes a novel enhanced AMBTC image compression method for digital color images which uses the characteristics of human visual system. The proposed compression method first transforms the RGB image into YCbCr color space and then divides each component of the image into non-overlapping blocks. To improve the imperceptibility of caused distortion due to AMBTC compression, the proposed method computes four quantization levels and 32 bits bit-planes for luminance component (Y) blocks whereas the blocks of the remaining two components (i.e., Cb & Cr) are represented by two quantization levels and only 8 bits bit-planes. At the receiving end, the receiver can use interpolation technique to predict the remaining 8 bits of the bit-planes of Cb and Cr components. Thus, the proposed method provides better quality stego-image than the related existing methods, Further, the required bit-rate is also reduced for all the test images irrespective of their characteristics.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于人眼视觉系统的增强AMBTC插值彩色图像压缩
利用人眼视觉系统的特点,提出了一种新的增强AMBTC图像压缩方法。提出的压缩方法首先将RGB图像转换为YCbCr颜色空间,然后将图像的每个分量划分为不重叠的块。为了提高AMBTC压缩引起的失真的不可感知性,该方法对亮度分量(Y)块计算4个量化级别和32位位平面,而其余两个分量(即Cb和Cr)块由2个量化级别和8位位平面表示。在接收端,接收机可以利用插值技术预测Cb和Cr分量位平面的剩余8位。因此,该方法提供了比现有方法更好的隐写图像质量,并且降低了所有测试图像所需的比特率,而不考虑其特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Data Classification by Reducing Bias of Domain-Oriented Knowledge Based on Data Jackets A Robust Automatic Algorithm for Statistical Analysis and Classification of Lung Auscultations Modified Dispersion Equation for Planar Open Tape Helix Travelling Wave Tube Experimental Analysis of Power Generation for Ultra-Low Power Wireless Sensor Nodes Using Various Coatings on Thermoelectric Energy Harvester A Novel Reconfigurable Patch Antenna with Parasitic Patch
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1